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Apache Kafka Source
Kustomer

Integrate Apache Kafka Source with Kustomer

Don't go through the pain of direct integration. RudderStack’s Apache Kafka Source integration makes it easy to send data from Apache Kafka Source to Kustomer and all of your other cloud tools.

Easy Apache Kafka Source to Kustomer integration with RudderStack

RudderStack’s open source Apache Kafka Source integration allows you to integrate RudderStack with your Apache Kafka Source to track event data and automatically send it to Kustomer. With the RudderStack Apache Kafka Source integration, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.

Popular ways to use Kustomer and RudderStack

Stream behavioral data

Easily stream data from your website or app to [integration, destination=TRUE] in real-time.

Customize data payloads

Modify payloads to match requirements in [integration, destination=TRUE].

Connect your pipelines

Automatically send user behavior data directly to Kustomer.

Frequently Asked Questions

With Rudderstack, integration between Apache Kafka Source and Kustomer is simple. Set up a Apache Kafka Source source and start sending data.
Pricing Apache Kafka Source and Kustomer can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
Timing can vary based on your tech stack and the complexity of your data needs for Apache Kafka Source and Kustomer.

Use the Kustomer integration with other popular sources

About Kustomer

Kustomer is a modern customer engagement platform designed for enterprises. It gives you a holistic view of your users and customer base, lets you provide best-in-class support, and engage with your customers through meaningful interactions.

About Apache Kafka Source

Apache Kafka is a popular distributed streaming platform. It allows you to handle large-scale workloads with high throughput and low latency. Apache Kafka is highly available and is used across the world for building real-time data pipelines and streaming applications.